AWS News Blog

Jeff Barr

Author: Jeff Barr

Jeff Barr is Chief Evangelist for AWS. He started this blog in 2004 and has been writing posts just about non-stop ever since.

Search and Interact With Your Streaming Data Using the Kinesis Connector to Elasticsearch

My colleague Rahul Patil wrote a guest post to show you how to build an application that loads streaming data from Kinesis into an Elasticsearch cluster in real-time. — Jeff; The Amazon Kinesis team is excited to release the Kinesis connector to Elasticsearch! Using the connector, developers can easily write an application that loads streaming […]

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ElastiCache T2 Support

As you may already know, Amazon Elastic Compute Cloud (EC2)‘s new T2 instance type provides a solid level of baseline performance and the ability to burst above the baseline as needed. As I wrote in my blog post, these instances are ideal for development, testing, and medium-traffic web sites. Today we are bringing the benefits […]

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AWS Week in Review – September 1, 2014

Let’s take a quick look at what happened in AWS-land last week: Monday, September 1 We celebrated Labor Day in the US, and launched nothing! Tuesday, September 2 We announced that you can now Query Your EC2 Instances Using Tag and Attribute Filtering. Wednesday,September 3 We announced that Version 13 of Hive is now Available for Elastic MapReduce. […]

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Launch Your Startup at AWS re:Invent

Sitting here at my desk in Seattle, I am surrounded by colleagues that are working non-stop to make this year’s AWS re:Invent conference the best one yet! I get to hear all about the keynotes, sessions, and the big party without even leaving my desk. In 2013, five exciting startups had the opportunity to launch […]

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Elastic MapReduce Now Supports Hive 13

I am pleased to announce that Elastic MapReduce now supports version 13 of Hive. Hive is a great tool for building and querying large data sets. It supports the ETL (Extract/Transform/Load) process with some powerful tools, and give you access to files stored on your EMR cluster in HDFS or in Amazon Simple Storage Service […]

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MySQL Cache Warming for Amazon RDS

Among many other responsibilities, a relational database system must make efficient use of main memory (RAM) for buffering and caching purposes. RAM is far faster and easier to access than SSD or magnetic storage; a properly sized and tuned cache or buffer pool can do wonders for database performance. Today we are improving Amazon RDS […]

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